System and method for learning and communicating implicit stylistic preferences from historical user interaction data in text-to-image prompt engineering

A user interface, comprising:

• one or more processors;
• and
• a memory encoded with instructions, which when executed by the one or more processors, causes the one or more processors to:
• generate a plurality of images for each of a plurality of user prompts received from a first user;
• generate a node tree diagram displaying one or more pluralities of images corresponding to one or mor user prompts, wherein the node tree diagram is based on one or more relationships between the pluralities of images;
• attribute a weight to a disliked plurality of images based on receiving input from a second user selecting a node associated with the disliked plurality of images from the node tree diagram;
• remove the node associated with the disliked plurality of images from the node tree diagram based on the weight;
• and
• generate a new set of images based on the second user's selecting the node associated with the disliked plurality of images.

A non-transitory machine-readable medium having instructions stored therein, which when executed by one or more processors, cause the one or more processors to:

• relate two or more pluralities of images based on input from a first user and transmit the related pluralities of images to a second user;
• attribute a positive weight to a preferred plurality of images based on user selection from the second user;
• generate a new set of images based on the second user's interactions with a node tree diagram displaying the preferred plurality of images;
• receive input from the second user selecting disliked nodes from the node tree diagram;
• and
• update the node tree diagram to indicate the preferred plurality of images and the positive weight.